THE USE OF PERFORMANCE MEASURES IN SMALL TO MEDIUM ENTERPRISES (SMEs) AN EXPLORATORY STUDY Brendan Phillips, Thomas Tan Tsu Wee and Tekle Shanka Curtin Business School Keywords: SMEs, performance measures, strategic marketing Abstract The need for organizations to align their performance measurement (PM) systems with their long term goals is well established in the literature (Kaplan and Norton, 1996; Wheelen and Hunger, 2002). As a result, many PM frameworks have emerged, one of which being that proposed by Kaplan and Norton (1992), emphasising financial and non-financial measures that are aligned with strategic objectives (Bremser and White, 2000; Hudson et al. 2001). Hudson et al. (2001) argue that measurement systems such as the balanced scorecard have been designed primarily for medium to large corporations and argue that the context of SME s requires a different approach. In line with this assertion, this exploratory study explores how financial and non-financial measures have been used in SMEs in Australia and South-East Asia. Exploratory factor analysis was performed and two factors were revealed from the 21 measurement items explaining 59% of the variance. The first factor (alpha 0.89) represents a customer service dimension of performance. The second factor (alpha 0.67) represents the financial dimension of performance. Significant differences were identified on the customer service dimension based on location of the organization and size of the organization. Results are discussed and directions for future research are proposed. Introduction The need for organizations to align their performance measurement (PM) systems with their long term goals is well established (Kaplan and Norton, 1996; Wheelen and Hunger, 2002). Many PM frameworks have emerged, the most popular being the balanced scorecard (Kaplan and Norton, 1992) which emphasizes financial and non-financial measures that are aligned with strategic objectives (Bremser and White, 2000; Hudson et al. 2001). Hudson et al. (2001) argue that measurement systems such as the balanced scorecard have been designed primarily for medium to large corporations and argue that the context of SME s requires a different approach. Despite the apparent simplicity of this management principle, it has proven to be an ongoing challenge to translate effectively into practice. Performance measurements link business strategy to operational performance thereby identifying critical factors of success in the long run (Kaplan and Norton, 1996). Wheelen and Hunger (2002) describe three types of performance measures necessary for effective strategic management namely, resource input (e.g. employee skills and organisational commitment), behavioural (e.g. operational process and compliance to procedures) and outcome measures (e.g. sales, profit, customer satisfaction, customer loyalty). Since the introduction of the BSC and other similar integrative measurement systems, there has been considerable attention paid to their adaptation to large corporations and government organizations around the world (Wheelen and Hunger, 2002; Ahn, 2001; Malmi, 2001; Butler, Letza & Neale, 1997). Owing to the fact that measurement systems like the BSC have been designed to be used in the context of large corporations, Hudson et al (2001) argue that 2455
additional problems exist when trying to develop PM systems for the context of SMEs. The unique characteristics of SMEs suggest that a different set of issues arise when attempting to develop and implement PM systems in this context. Objectives of Study This paper explores the use of financial and non-financial performance measures among 270 SMEs based in Australia and South East Asian countries. Organisation size ranges between 10 and 250 employees which is consistent with current SME definitions (European Commission, 1996, cited in Hudson et al., 2001). Whilst there has been considerable attention paid to the use of performance measures in large enterprises and government departments, relatively little research has been conducted on performance measures in SMEs. This is in spite of the fact that SMEs have very unique characteristics compared to large corporations (Hudson et al. 2001). The characteristics include the size of the companies, a simplified product and service offerings in homogeneous or niche markets, a centralized organizational structure with a lack of specialized occupations and departments. SMEs account for over 95% of all businesses and 85% of all new jobs in developed economies (Wheelen and Hunger, 2002; Hanson et al., 2002). This exploratory study aims to identify the dimensions of performance measurement that are being used and the differences in the use of performance measures between organisations of different sizes, age and business location (country) and industry type. Research Methodology An initial exploratory study was conducted on 99 organisations based in Australia and South East Asian countries to determine the range and type of performance measures used in the SMEs in these locations (Phillips and Shanka, 2002). The results of this initial study were used to develop a standard survey instrument for the current study. For this new study, a standard survey questionnaire was used and administered through faceto-face interviews with top management. A total of approximately 1000 telephone requests for interviews were made to organisations to take part in the survey in 4 countries namely Hong Kong, Singapore, Malaysia and Australia. After an initial period, the management of these companies were contacted by phone to remind them of the interviews and to set a date and time for the interviews to take place. A total of 270 interviews were successfully conducted by trained interviewers in each country. The questionnaire itself consisted of scale items to identify performance measures being used, the frequently of usage, and the importance of each measure. Additional questions included demographic characteristics of the participants, the organisation s industry classification, age of the organization, scope of the organisation s activities (i.e. local, international etc.), number of staff, and annual turnover. As mentioned a total of 270 businesses participated in the survey and the completed survey data were analysed using the SPSS statistical package version 11.0. Results and Discussion Profiles of organisations The majority (95.6%) were represented by for-profit enterprises. Apart from Malaysian organisations (4.4%), there was a fairly even representation of organisations from Hong Kong (38.1%), Western Australia (31.1%) and Singapore (26.3%). 51% of organisations were established from 1990 onwards. The three main industry sectors represented were services 2456
(46.4%), wholesale and retail trade (27.7%) and manufacturing/construction (25.8%). 29.9% had 15 or less employees, 20.5% had 16 to 17 employees, 24.3% had 28 to 65 employees and 25.4% had more than 65 employees. Performance measures currently in use The mean scores on the degree of importance of the 21 performance measure scale items ranged from a high of 6.4 (profit and loss) to a low of 4.7 (employee satisfaction/turnover, new product/revenue growth and client referrals) (Table 1). The most popular measures used monthly were sales/revenue (76% of organisations), followed by accounts receivable/payable (72%), inquiry/complaint follow-up (61%) and profit/loss (60%). Not surprising was the finding that it was most common to use employee performance measures on an annual basis (35%). Of interest was the finding that 48% of organisations did not have any measure for client referrals as a new source of customers. Other areas not measured included customer feedback, new product revenues (31%), employee satisfaction/turnover (30%), and customer retention/loyalty/profitability (29%). The three scale items with lowest mean scores that were also reported as not being in use together with customer retention/loyalty/profitability and employee training and development were dropped from further analyses due to the higher percentage of respondents indicating that these measures were not in use. Table 1. Mean scores and usage patterns of Performance Measures Measures Mean* Importa nce Usage patterns (Per cent mentioning) 1 2 3 4 5 Profit and loss 6.4 60.0 15.0 8.0 16.0 1.0 Sales/revenue 6.3 76.0 10.0 5.0 7.0 1.0 Accounts receivable/payable 5.5 72.0 10.0 6.0 4.0 8.0 Inquiry / complaint follow up 5.5 61.0 8.0 7.0 2.0 21.0 Customer retention/loyalty/profitability 5.4 28.0 16.0 14.0 13.0 29.0 Customer complaints/returns 5.3 49.0 8.0 6.0 6.0 31.0 Cost efficiency 5.3 42.0 20.0 11.0 9.0 18.0 Operational efficiency/effectiveness 5.2 38.0 19.0 13.0 8.0 22.0 Quality/continuous improvement 5.2 35.0 18.0 11.0 11.0 25.0 Conformance to delivery standards/service request 5.2 40.0 18.0 9.0 4.0 29.0 Conformance to service standards 5.2 34.0 16.0 10.0 10.0 30.0 Customer feedback/survey 5.2 33.0 12.0 9.0 12.0 33.0 Risk management/quality control 5.1 36.0 21.0 8.0 12.0 23.0 Employee performance management 5.1 18.0 15.0 18.0 35.0 14.0 Employee training and development 4.9 20.0 13.0 19.0 20.0 28.0 Sales/inquiries/market share 4.9 32.0 15.0 11.0 15.0 27.0 Financial ratios 4.9 29.0 18.0 8.0 18.0 27.0 Inventory control 4.8 49.0 9.0 9.0 8.0 25.0 Employee satisfaction/turnover 4.7 16.0 12.0 15.0 27.0 30.0 New product revenues/growth 4.7 22.0 18.0 12.0 17.0 31.0 Client referrals 4.7 32.0 9.0 6.0 5.0 48.0 *On a scale 1 = least important to 7 = most important. Usage pattern: 1 = monthly, 2 = quarterly, 3 bi-annually, 4 = annually, 5 = not in use. 2457
Factor analysis Principal component analysis with varimax rotation was performed on the 16 measurement items. Factorability of the items was verified by the use of KMO and Bartlett s test of sphericity (KMO =.864, _ 2 = 719.470, df = 55, p <.001). Two components were extracted that explained 59% of the variance (Table 2). The first component consisting of seven items (eigen value = 4.810, _ = 0.89) accounted for 44% of the variance and represents measures related to the customer service perspective. The second component, consisting of four items (eigen value = 1.678, _ = 0.67) accounted for 15% of the variance represents measures related to financial perspective. Table 2. Principal Component Matrix Performance Measures Customer feedback/survey Customer complaints/returns Inquiry / complaint follow up Quality/continuous improvement Conformance to service standards Sales/inquiries/market share Employee performance management Sales/revenue Profit and loss Accounts receivable/payable Financial ratios Dimensions 1 Customer service 2 Financial.835.820.801.770.766.690.610.825.767.628.619 Eigen value Per cent of Variance Cronbach s alpha coefficient Summated mean score Differences in performance measures dimensions 4.810 43.7.8876 5.2 1.678 15.3.6687 5.8 One-way between groups ANOVA test showed statistically significant differences on the customer service dimension for location of business (F = 9.99, sig. =.000). The mean differences were significant between businesses located in Australia and those located in Singapore or Hong Kong. Australian businesses scored significantly higher mean (M = 5.7) compared with those from Singapore (M = 5.2) or Hong Kong (M = 4.8). Furthermore, statistically significant difference was reported on the customer service dimension for employee size (F = 4.026, sig. =.008). The mean scores for organization with 15 or less employees were significantly lower (M = 5.0) compared with those organizations that employ 28 to 65 staff (M = 5.6). The latter group also had significantly higher mean score compared with organizations with 16 to 27 employees (M = 4.9). However, no statistically significant difference was reported for age of business or length of time respondents were in current position, current organisations or current industry. Neither was there any statistically significant difference between sectors of the industry (manufacturing/mining/construction, wholesales and retail trade, and services). 2458
Implications and Conclusion This exploratory study has identified two dimensions of performance measurement in use by SME s namely customer service and financial dimensions. These two dimensions explain 59% of the variance. It is noted that only two of Kaplan and Norton s (1992) dimensions of performance were identified in this study. Statistically significant differences were identified in the degree of importance for using measures on the customer service dimension based on the location and size of the organisation. Australian organisations reported higher levels of importance for using customer service measures than Hong Kong and Singapore SME s. Larger SME s with 28 to 65 employees also reported higher levels of importance for using customer service measures than organisations with 27 or less employees. These results appear to support the earlier findings by Llonch et al. (2002) who identified differences between Spain and UK organizations in the use of measures of marketing success. Findings also lend some support for the argument by Hudson et al (2001) that the organisation s size influences the measurement system and measures used. It would appear that smaller size companies tend to use basic financial measures and a modicum of non financial measures such as customer feedback and customer retention/loyalty/profitability (29%). This would suggest an emphasis among these companies on financial indicators and a neglect of non financial but nevertheless important measures on marketing and customer issues. This lack of marketing or customer orientation has serious implications for these companies if they wish to be proactive, build customer loyalty, increase its market share or be export oriented in order to gain market expansion. No significant differences were identified between organizations based on their age. This appears to contradict the proposition by Thain (1969) cited in Wheelen and Hunger (2002) that organizations of different stages of corporate development apply different measurement and control systems and key performance indicators. Some limitations of this study are non-random sample used in that only those approached and who agreed to participate were included. The face-to-face interview process may be another limitation. Future studies will confirm these findings with larger sample sizes. Subsequent to this, only those items loading on the two components identified in this study will be used in future surveys. In addition, the future survey will include as a dependent variable, overall perceived performance in relation to the competition. This will enable some additional important and interesting relationships to be explored between dimensions of performance measured and self reported organisational performance as an outcome. References Ahn, H. (2001). Applying the balanced scorecard concept: an experiential report. Long Range Planning, 34: 441-461. Bremser, W.G. and White, L.F. (2000). An experiential approach to learning about the balanced scorecard. Journal of Accounting Education, 18: 241-255. Butler, A., Letza, S.R. and Neale, B. (1997). Linking the balanced scorecard to strategy. Long Range Planning, 30(2): 242-253. Fisher, J. (1992). Use of nonfinancial performance measures. Journal of Cost Management, 6(1): 31-38. 2459
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